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TensorStore for High-Performance, Scalable Array Storage

Posted by Jeremy Maitin-Shepard and Laramie Leavitt, Software Engineers, Connectomics at Google Many exciting contemporary applications of computer science and machine learning (ML) manipulate multidimensional datasets that span a single large coordinate system, for example, weather modeling from atmospheric measurements over a spatial grid or medical imaging predictions from multi-channel image intensity values in a …

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Detect population variance of endangered species using Amazon Rekognition

Our planet faces a global extinction crisis. UN Report shows a staggering number of more than a million species feared to be on the path of extinction. The most common reasons for extinction include loss of habitat, poaching, and invasive species. Several wildlife conservation foundations, research scientists, volunteers, and anti-poaching rangers have been working tirelessly …

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How Amazon Search reduced ML inference costs by 85% with AWS Inferentia

Amazon’s product search engine indexes billions of products, serves hundreds of millions of customers worldwide, and is one of the most heavily used services in the world. The Amazon Search team develops machine learning (ML) technology that powers the Amazon.com search engine and helps customers search effortlessly. To deliver a great customer experience and operate …

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What’s New with Google’s Unified, Open and Intelligent Data Cloud

We’re fortunate to work with some of the world’s most innovative customers on a daily basis, many of whom come to Google Cloud for our well-established expertise in data analytics and AI. As we’ve worked and partnered with these data leaders, we have encountered similar priorities among many of them: to remove the barriers of …